Mumbai: Maths professor-turned-entrepreneur Chetan Dube believes in boldly going where few technology companies have gone before—stretching the capabilities of artificial intelligence (AI) with his company IPsoft’s Amelia and Apollo platforms.

Dube, who will be speaking at EmTech India 2017—an iconic emerging technology conference organised by Mint and MIT Technology Review—on 10 March in New Delhi, talks about his love of math, the chances of cloning a human brain and the partnership with Accenture Plc. to bring the benefits of ‘digital labour’ to global corporations. Edited excerpts:

Tell us a bit about your academic background and how you grew to love maths and computer science.

Maths was always beautiful to me, as everything made sense. It provides us the foundational tool to know that we are still expanding and galaxies are moving farther away from each other, and computers have enabled man to proverbially boldly go where it was not conceived that man could go before. Without the two, man would not have been able to explore the magical world around us to its fullest. I took my love for the topics to a haven for maths and computer science—the Courant Institute of Mathematical Sciences at New York University (NYU).

What inspired you to set up IPsoft rather than taking up a job or continuing research?

The research I was doing at NYU centred round modelling of a system engineer’s brains with deterministic finite state machines. I remember a summer afternoon in 1998 suggesting to my adviser, Prof. Dennis Shasha, that given a couple of summers, we should be able to extend our research to one on artificial general intelligence (AGI). Prof. Shasha wisely reminded me that even the father of AI, John McCarthy, gave up on that, stating that the problem turned out to be a lot harder than anticipated. But the seeds of an AGI future had been planted. We were drawn inexplicably and compellingly by a future where man and machine would work together to create a beautiful planet—and IPsoft was born. Here we are today, 18 summers later, finally starting to approach that ever elusive Turing horizon.

In your younger days, you even thought that it was possible to clone a human brain in the near future. Now that AI, neuroscience and neuro-computing have matured, how far are human beings from actually performing such a task?

(Alan) Turing had said in 1949, “I propose to ask the question, ‘Can machines think?’” Man has wrestled with that challenge ever since. We have had the winters and springs of AI. Cloning the human brain can be approached in a few different ways. One fundamental way is to emulate each one of the neurons through neurosynaptic cores. This approach is foundational, but still some distance from maturity. Another approach examines man’s quest for flight, wherein man succeeded when he stopped trying to emulate birds with flapping wings and started to apply the principles of aerodynamics. The idea is to fly. Rather than trying to recreate God’s creation, can we simulate the output of human brain by emulating neocortical activities and cloning its semantic, episodic and affective memories? The latter approach, utilizing semantically conditioned deep neural networks, has shown maturity to realizing that Turing horizon.

How does Apollo compare with IBM’s Watson, Tata Consultancy Services’ Ignio or Wipro’s Holmes for that matter? And how does Amelia compare with similar products from Apple (Siri) and Google?

The chatbot category is overflowing with companies claiming they are offering you the transformative power of AI in your pocket. So many of these, however, are very simple instruction-based agents that have simply been trained to interpret words in order to fulfil commands. On another level, there are AI offerings engineered to mine and analyse data in ways that were previously impossible. These platforms place a new type of decision-making tool into the hands of humans.

We have developed Amelia to comprehend a conversation just like a human. This means understanding the concepts that are being conveyed in the unique context of each exchange in dialogue and successfully identifying the intention of that customer. It then requires that Amelia can draw on her knowledge to determine what steps she should take in order to help resolve the customer’s query. Lastly, it requires that Amelia learns all the time as we do through her own experience and by observing her colleagues rather than being programmed. As humans, we interact on an emotional level and so this, too, is a key aspect of Amelia’s uniqueness. She understands the emotional context of the dialogues she has and is able to formulate her responses accordingly.

In Apollo, we marry Amelia’s cognitive abilities with an autonomic backbone to create an end-to-end management of IT infrastructure. Rather than automating functionsto assist the manual processes that are common today, Apollo turns the way in which we think about ITSM (IT service management) on its head. Its core design principle is to optimize the use of advanced AI technologies in order to execute entire processes and only introduce manual steps to manage exceptions. Once any such manual task is completed, however, Apollo self-generates a new set of steps that allow it to automate similar requests in future.

How’s the reception for Amelia within the enterprise?

In the past year, we have seen interest from executives pivot from curiosity about advancement of science to urgency in demand for Amelia to transform operations and customer experience. We are engaged on Amelia implementation projects with more than 50 leading global brands and are expanding our team rapidly in order to fulfil the swell in demand we have witnessed. We have, for instance, trained a great number of Accenture’s specialists in how to work with Amelia. Not only does this training equip them with the knowledge to implement Amelia successfully, it also gives them the insight required to identify the areas where her capabilities can be used to transform their clients’ performance.

While there are those who believe in the potential of AI and its applications, a sizeable number of people including Stephen Hawking, Bill Gates and Elon Musk have expressed fears that AI-powered machines could rule over humans. What’s your take on this subject?

I do not share these views. The science itself is still, relatively speaking, within its infancy. Notwithstanding that, I do agree that we need to examine a new and evolving set of ethical principles that govern the relationship between man and machine. Our human responsibilities will grow, not diminish, through the employment of digital labour. We must embark on defining those new responsibilities with an enlightened mindset—the advancement of the technology itself will not be reversed.

How well are Indian companies across sectors handling AI and automation?

The Indian IT industry can only advance into the digital economy era if it is prepared to let go of the manual offshore models that gave rise to its original growth. Future economies will not compete on the basis of accessing cheaper and cheaper labour. This is a fundamental change and strikes at the root of Indian IT’s identity. Despite the huge pool of talent and intellect in India, we have seen the tech giants reduce its potential in order to fuel a global back-office factory. It’s time now to infuse our universities and corporates with the skills required for the future: cognitive engineers, data scientists, autonomic specialists, and creative developers of a new user experience. The fear of cannibalizing existing revenue streams is a dangerous inhibitor of change. While everyone appears to pay lip service to incorporating AI, very little is being done to align resources to a very different set of offerings.